class_docstr: The Ray Serve integration engine needs to have a working connection to Ray Serve. For this:
      - A Ray Serve server should be running
  
  Example:
      
code: def predict(self, df, args=None):
      args = self.model_storage.json_get(
          "args"
      )  # override any incoming args for now
      resp = requests.post(
          args["predict_url"],
          json={"df": df.to_json(orient="records")},
          headers={
              "content-type": "application/json; format=pandas-records"
          },
      )
      answer = resp.json()
      predictions = pd.DataFrame({args["target"]: answer["prediction"]})
      return predictions
  
file_path: mindsdb/mindsdb/integrations/handlers/ray_serve_handler/ray_serve_handler.py
imports: import requests
  from typing import Dict, Optional
  import pandas
  from mindsdb.integrations.libs.base import BaseMLEngine
label_desc: Use image node_id 3 for calling the RayServeHandler obj's underlying member method code with example usage: obj.predict(df, args) and returns: predictions